Method and device for processing blood vessel image on basis of user input

ABSTRACT

The present disclosure relates to a method, performed by a processor, for processing a blood vessel image from a blood vessel image, the method comprising the steps of: extracting a target blood vessel from a blood vessel image; determining a region of interest (ROI) in an extraction result of the target blood vessel on the basis of a first input received from a user; and within the determined ROI, identifying an error portion in the extraction result on the basis of a second input received from the user, and correcting the identified error portion.

TECHNICAL FIELD

The following description relates to a method for processing a bloodvessel image.

BACKGROUND ART

Angiography images are widely used to diagnose error portions withinblood vessels by observing main blood vessels and perform necessaryprocedures and measures. Conventionally, image processing engines forautomatically identifying main blood vessels from a blood vessel imagehave been used in order to increase convenience and quantify a diagnosisresult. For example, a Caas QCA engine from Pie Medical Imaging B. V.may find and display main blood vessels in the angiography images. Onthe other hand, the main blood vessels extracted from the engine oftenshow errors, such as blood vessel portions (misidentification) otherthan the main blood vessels to be extracted, a portion (disconnection)to be disconnected, or the like. Therefore, in clinical practices, anidentification result obtained by first extracting the main bloodvessels from the engine is not used as it is, but manpower is input tocheck the angiography image, and the errors are directly corrected bythe manpower and then the corrected errors are used and stored.

The above-mentioned background art is possessed or acquired by theinventor in the process of deriving the disclosure of the presentapplication and cannot necessarily be said to be a known technologydisclosed to the general public prior to the present application.

DISCLOSURE OF THE INVENTION Technical Goals Technical Solutions

According to an aspect of the present disclosure, there is provided amethod for processing a blood vessel image from performed by aprocessor, the method including the steps of: extracting a target bloodvessel from a blood vessel image; determining a region of interest (ROI)in an extraction result of the target blood vessel on the basis of afirst input received from a user; and identifying an error portion inthe extraction result on the basis of a second input received from theuser, and correcting the identified error portion within the determinedROI.

In an example embodiment, the determining of the ROI may includedetermining a shape of the ROI on the basis of points in which the firstinput is detected.

In an example embodiment, the correcting of the error portion mayinclude correcting the error portion on the basis of the plurality ofpoints of the second input, in response to a case where the second inputis detected from the plurality of points within the ROI.

In an example embodiment, the correcting of the error portion on thebasis of the plurality of points may include detecting whether there isa discontinuity portion in points through which the second input passes,while a point corresponding to the second input moves along a regionextracted as the target blood vessel; and connecting discontinuedportions along a movement trajectory of the second input in response toa case where the discontinuity portion is detected.

In an example embodiment, the correcting of the error portion on thebasis of the movement trajectory may include determining a blood vesselbranch located out of a region corresponding to the movement trajectoryof the second input among the blood vessel branches connected with thebranch point as a misidentification portion, in response to a case wherethe point corresponding to the second input moves to a region out of thetarget blood vessel from the branch point within the region extracted asthe target blood vessel; and replacing the blood vessel branch with ablood vessel branch indicated by the second input out of the targetblood vessel and correcting the remaining extraction result on the basisof the replaced blood vessel branch.

In an example embodiment, the correcting of the error portion mayinclude identifying the error portion from the extraction result of thetarget blood vessel in response to the determining of the ROI andcorrecting the identified error portion; and providing the user with acorrection result of the error portion.

In an example embodiment, the providing of the user with the correctionresult may include providing the user with one or more candidatebranches in response to a case where the error portion is amisidentification portion; and replacing a branch corresponding to theerror portion with the selected branch in response to a case ofreceiving a pointing input for one branch among the one or morecandidate branches from the user.

In an example embodiment, the providing of the user with the correctionresult may include connecting a region corresponding to a blood vesselbranch corresponding to a start point of a user input and a regioncorresponding to a blood vessel branch corresponding to an end point ofthe user input, in response to a case where the user input is detectedin a plurality of points with respect to the correction result.

In an example embodiment, the correcting of the error portion mayinclude identifying the error portion on the basis of at least one ofblood vessel structure data related to the target blood vessel,curvature information of the target blood vessel, diameter informationof the target blood vessel, and brightness information of the targetblood vessel, in response to a case where the ROI is determined.

In an example embodiment, the correcting of the error portion mayinclude correcting the error portion on the basis of at least one ofblood vessel structure data related to the target blood vessel,curvature information of the target blood vessel, diameter informationof the target blood vessel, and brightness information of the targetblood vessel, in response to a case where the error portion isidentified.

In an example embodiment, the correcting of the error portion mayinclude generating a plurality of new extraction results for the targetblood vessel in response to a case where the error portion isidentified; and selecting one extraction result indicated by theselection input among the plurality of new extraction results inresponse to the selection input of the user.

According to another aspect of the present disclosure, there is provideda device for processing the blood vessel image including: an imagereceiver for receiving a blood vessel image; and a processor forextracting a target blood vessel from a blood vessel image, determininga region of interest (ROI) in an extraction result of the target bloodvessel on the basis of a first input received from a user, andidentifying an error portion in the extraction result on the basis of asecond input received from the user, and correcting the identified errorportion within the determined ROI.

Advantageous Effects

The method for processing the blood vessel image performed by the devicefor processing the blood vessel image according to the exampleembodiment can extract a target blood vessel corresponding to main bloodvessels from the blood vessel image in which the contrast agent isinserted. In addition, the device for processing the blood vessel imagecan determine a region of interest (ROI) by receiving a user input andidentify and correct an error portion on the basis of the input receivedfrom the user in the ROI.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a flowchart illustrating a method for processing a bloodvessel image according to an example embodiment.

FIGS. 2A to 2C are diagrams illustrating blood vessel images in which atarget blood vessel and a region of interest (ROI) are displayed,according to an example embodiment.

FIG. 3 illustrates an example in which an error portion occurs in anextraction result of a target blood vessel according to an exampleembodiment.

FIGS. 4 to 6 illustrate a method for identifying an error portion of theextraction result and correcting the identified error portion on thebasis of a second input received from a user in an ROI.

FIGS. 7 and 8 illustrate a method for correcting an error portionaccording to an example embodiment.

FIG. 9 illustrates a method for identifying an error in a target bloodvessel using a topology of blood vessel structure data on the basis ofnodes corresponding to blood vessel branches.

FIGS. 10 and 11 illustrate a method for correcting an error portionaccording to an example embodiment.

FIG. 12 illustrates a method for identifying and correcting an error ina target blood vessel using curvature information of the target bloodvessel.

FIG. 13 illustrates a method for identifying and correcting an error ina target blood vessel using diameter information of the target bloodvessel.

FIG. 14 illustrates a method for identifying and correcting an error ina target blood vessel using brightness information of the target bloodvessel.

FIG. 15 is a block diagram schematically illustrating a device forprocessing a blood vessel image according to an example embodiment.

BEST MODE FOR CARRYING OUT THE INVENTION

Specific structural or functional descriptions of example embodimentswill be disclosed for purposes of only examples, and may be changed andimplemented in various forms. Accordingly, the example embodiments arenot limited to a specific disclosure form, and the scope of the presentspecification includes changes, equivalents, or substitutes included inthe technical spirit.

Terms such as first or second may be used to describe variouscomponents, but these terms should be interpreted only for the purposeof distinguishing one component from other components. For example, afirst component may be referred to as a second component, and similarly,the second component may be referred to as the first component.

It should be understood that, when it is described that a component is“connected” to the other component, the component may be directlyconnected to or access the other component or a third component may bepresent therebetween.

The singular expression includes the plural expression unless thecontext clearly dictates otherwise. In the present specification, itshould be understood that a term such as “comprise”, “have”, or the likeis intended to designate that a feature, a number, a step, an operation,a component, a part, or a combination thereof described in thespecification exists, but it does not preclude the possibility ofexistence or addition of one or more other features, numbers, steps,operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical orscientific terms, have the same meaning as those commonly understood bythose skilled in the art to which the example embodiments belong. Termssuch as those defined in a commonly used dictionary should beinterpreted as having a meaning consistent with the meaning in thecontext of the related art, and should not be interpreted in an ideal orexcessively formal meaning unless explicitly defined in the presentapplication. Hereinafter, example embodiments will be described indetail with reference to the accompanying drawings. Like referencenumerals illustrated in the respective drawings designate like members.

FIG. 1 is a flowchart illustrating a method for processing a bloodvessel image according to an example embodiment.

First, in step 110, a device for processing a blood vessel image mayextract a target blood vessel from a blood vessel image. The targetblood vessel may also be referred to as a main blood vessel. Accordingto an example embodiment, an image receiver of the device for processingthe blood vessel image may receive a blood vessel image photographed bya blood vessel image photographing device. The blood vessel image is animage obtained by photographing a blood vessel of a living body and maybe generated using a coronary angiography (hereinafter, CAG) imageand/or a magnetic resonance imaging (MRI). For example, the blood vesselimage may be an image obtained by performing X-ray imaging of a livingbody into which a contrast agent is injected.

According to an example embodiment, the device for processing the bloodvessel image may extract a target blood vessel from the blood vesselimage on the basis of a machine learning model. The machine learningmodel is at least one model having a machine learning structure designedto extract the target blood vessel from the blood vessel image inresponse to an input of the blood vessel image, and for example, mayinclude a neural network. The device for processing the blood vesselimage may calculate an extraction result of the target blood vessel byperforming an operation according to the above-described machinelearning model on the received blood vessel image. For example, outputdata of the machine learning model may include a score corresponding toa possibility (e.g., probability) that each pixel in a plurality ofpixels of the blood vessel image indicates the target blood vessel. Thedevice for processing the blood vessel image may generate an extractionresult of the target blood vessel by determining pixels having a scoreof a threshold value or more in output data as the target blood vessel.As another example, the output data of the machine learning model is atarget blood vessel area segmented from the blood vessel image, and mayinclude pixels extracted as the target blood vessel among the pluralityof pixels of the blood vessel image. The extraction result of the targetblood vessel may be, for example, a set of pixels extracted as thetarget blood vessel of pixels of the blood vessel image and/or an image(e.g., a target blood vessel image) corresponding to the target bloodvessel area segmented from the blood vessel image.

For reference, the neural network may include a deep neural network(DNN). The DNN may include a fully connected network, a deepconvolutional network, a recurrent neural network, and the like. Theneural network may perform object classification, object recognition,radar image recognition, and the like by mapping input data and outputdata in a non-linear relationship to each other based on deep learning.The deep learning is a machine learning technique for solving problemssuch as object recognition from a big data set and may map input dataand output data to each other through supervised or unsupervisedlearning. In the case of the supervised learning, the aforementionedmachine learning model may be trained on the basis of training dataincluding a pair of a training input (e.g., a blood vessel image fortraining) and a training output (e.g., a ground truth image segmented tothe target blood vessel by experts and the like with respect to theblood vessel image for training) mapped in the corresponding traininginput. For example, the machine learning model may be trained to outputthe training output from the training input. The machine learning model(hereinafter, a ‘temporary model’) during training may generate atemporary output in response to the training input, and may be trainedso that a loss between the temporary output and the training output(e.g., a ground truth value) is minimized. During the training process,parameters (e.g., connection weights between nodes/layers in the neuralnetwork) of the machine learning model may be updated according to theloss.

However, an example in which the machine learning model directlyextracts the target blood vessel from the blood vessel image has beendescribed, but the present disclosure is not limited thereto. Forexample, the machine learning model may include a whole blood vesselextraction model and a target blood vessel extraction model. The wholevessel extraction model may be a model designed to extract a whole bloodvessel area from the blood vessel image. The target blood vesselextraction model may be a model designed to extract a target bloodvessel area from an image (e.g., a whole blood vessel image) indicatingthe whole blood vessel area. In addition, instead of the whole vesselextraction model, the device for processing the blood vessel image mayalso extract the whole blood vessel area by detecting a boundary on thebasis of a difference in grayscale level between pixels in the bloodvessel image and neighboring pixels. Illustratively, the device forprocessing the blood vessel image may detect the corresponding pixel asa boundary when a gradient value of grayscale levels of an arbitrarypixel and neighboring pixels is greater than a threshold gradient value.Accordingly, the device for processing the blood vessel image may detecta region in which the grayscale level is rapidly changed as theboundary. The device for processing the blood vessel image may alsoextract a target blood vessel image using the target blood vesselextraction model from the whole blood vessel image extracted on thebasis of the gradient value of the grayscale level.

Furthermore, the device for processing the blood vessel image may alsoselectively use a machine learning model to be used for extraction ofthe target blood vessel from among a plurality of machine learningmodels according to the shape and type of the blood vessel and/or ablood vessel area. According to an example embodiment, the device forprocessing the blood vessel image may store a plurality of machinelearning models for each type of blood vessel (e.g., left main coronaryartery (LM), left anterior descending artery (LAD), left circumflexartery (LCX), and right coronary artery (RCA)) and/or for each bloodvessel area (e.g., proximal region, mid region, and distal region). Forreference, the blood vessel area may be classified into a proximalportion, a middle portion, and a distal portion according to a distancefrom a blood vessel point into which a catheter is inserted, but is notlimited thereto. The blood vessel area may also be classified accordingto a ratio of a distance from a point where the contrast agent isinjected into a blood vessel insertion unit and a distance from a bloodvessel end into which the contrast agent may be injected in order toobtain the blood vessel image. For example, the device for processingthe blood vessel image may select a type of blood vessel to be extractedand load a machine learning model corresponding to the identified typeof blood vessel. The device for processing the blood vessel image maygenerate an extraction result of a target blood vessel corresponding tothe type of blood vessel selected from the blood vessel image using theloaded machine learning model. Illustratively, the device for processingthe blood vessel image may store a machine learning model correspondingto a plurality of cardiovascular types (e.g., one right coronary arteryand two left coronary arteries). Each of the machine learning modelscorresponding to the plurality of cardiovascular types may be trained onthe basis of training data corresponding to the correspondingcardiovascular type. Trained parameters of the machine learning modelsfor each cardiovascular type may be different from each other, andfurthermore, machine learning structures (e.g., convolutional neuralnetworks, U-net structures, etc.) may be different from each other. Forconvenience of description, the machine learning models in whichparameters and/or machine learning structures are distinguished for eachtype of blood vessel have been described, but the present disclosure isnot limited thereto. The device for processing the blood vessel imagemay also be used for extracting the target blood vessel by storing theplurality of machine learning models that are distinguished from eachother by the shape and type of the blood vessel, and/or the blood vesselarea and selectively loading a required blood vessel model.

In addition, in step 120, the device for processing the blood vesselimage may determine a region of interest (ROI) for the extraction resultof the target blood vessel on the basis of a first input received fromthe user. The ROI may indicate a partial region selected by the user inthe blood vessel image for analysis of the blood vessel image. Thedevice for processing the blood vessel image may focus processing on theblood vessel image on the ROI by determining the ROI. The detaileddescription of the ROI will be described below in FIG. 2 .

In step 130, the device for processing the blood vessel image mayidentify an error portion of the extraction result on the basis of asecond input received from the user within the determined ROI andcorrect the identified error portion. The error portion may include adiscontinuity portion and/or a misidentification portion. Thediscontinuity portion may indicate a portion where among target bloodvessel areas extracted as the target blood vessel and/or pixelsindicating the target blood vessel, at least one area and/or at leastone pixel is separated or spaced apart from other areas and/or otherpixels. The misidentification portion may indicate a portion where anarea and/or pixels corresponding to a blood vessel other than the targetblood vessel to be actually extracted from the blood vessel image areerroneously extracted as the target blood vessel.

For example, the device for processing the blood vessel image mayidentify and correct an error portion on the basis of a movementtrajectory of the second input in response to a case where a point atwhich the second input is detected moves within the ROI. As anotherexample, the second input may represent a pointing input. The device forprocessing the blood vessel image may also identify and correct an errorportion on the basis of a region between a start point and an end pointcorresponding to the pointing input. As another example, the device forprocessing the blood vessel image may identify and correct a point atwhich the second input is maintained as the error portion, in responseto a case where the point at which the second input is detected ismaintained for a threshold time or more at a point within the ROI. Thecorrection on the basis of the second input will be described withreference to FIGS. 4 to 6 below.

FIGS. 2A to 2C are diagrams illustrating blood vessel images in which atarget blood vessel and a region of interest (ROI) are displayed,according to an example embodiment.

The device for processing the blood vessel image may photograph bloodvessel images 201, 202, and 203. The device for processing the bloodvessel image may receive the blood vessel images 201, 202, and 203 froma blood vessel image photographing device. The device for processing theblood vessel image may extract target blood vessels 211, 212, and 213from the received blood vessel images 201, 202, and 203. The device forprocessing the blood vessel image may extract the target blood vessels211, 212, and 213 on the basis of a machine learning model. The devicefor processing the blood vessel image may determine a region of interest(ROI) 221 for the extraction result of the target blood vessel on thebasis of a first input 231 received from the user. The device forprocessing the blood vessel image may determine a shape of the ROI onthe basis of points at which the first input is detected. The device forprocessing the blood vessel image may detect a start point 232 of thefirst input 231 and an end point 233 of the first input 231 receivedfrom the user. The first input 231 may be detected at the start point232 and then maintained until the end point 233 and released at the endpoint 233.

Referring to FIG. 2A, the device for processing the blood vessel imagemay receive a drag input from the start point 231 to the end point 233as the first input 231 from the user. The drag input may represent aninput of clicking or touching any point (e.g., the start point 232) onthe display, moving while the click or touch is maintained, andreleasing the click or touch at another point (e.g., the end point 233).In addition, the device for processing the blood vessel image maydetermine the ROI 221 in a predefined shape between the detected startpoint 232 and end point 233. For example, the ROI 221 may be determinedsuch that the start point 232 and the end point 233 are disposed on aboundary of the ROI 221. As illustrated in FIG. 2A, the predefined shapeof the ROI 221 may be a rectangle, but is not limited thereto, and maybe a polygon or a circle. The device for processing the blood vesselimage may output a temporary ROI 220, which is a region between a pointwhere the detection of the first input 231 starts and a point where thefirst input 231 is currently detected, through the display, to providethe output temporary ROI 220 to the user. The device for processing theblood vessel image may provide feedback to the user before determiningthe ROI 221 by providing the temporary ROI 220 to the user. When thedetection of the first input 231 ends, the device for processing theblood vessel image may determine the ROI 221 in a predefined shapebetween the start point 232 where the first input 231 is detected andthe end point 233 of the first input 231 to output and provide thedetermined ROI 221 to the user through the display.

Referring to FIG. 2B, the device for processing the blood vessel imagemay receive a first input including a plurality of inputs from the user.The plurality of inputs included in the first input may represent aclick or a touch on an arbitrary point on the display. The device forprocessing the blood vessel image may determine, as the ROI 222, aregion in a polygon formed by continuously connecting points 241, 242,and 243 on the display corresponding to the plurality of inputs in astraight line according to a user input, according to the first inputreceived from the user. The device for processing the blood vessel imagemay provide the user with a partial shape of a polygon formed from thepoint where the detection of the first input starts to the point wherethe first input is currently detected.

Referring to FIG. 2C, the device for processing the blood vessel imagemay receive, as the first input, a drag input from a start point 251 toan end point 251 which is the same point as the start point from theuser. The device for processing the blood vessel image may determine, asa ROI 223, a region in a free curve corresponding to a drag input of theuser having the same start point and end point. The device forprocessing the blood vessel image may provide the user with a partialshape of a free figure formed by the free curve formed from the pointwhere the detection of the first input starts to the point where thefirst input is currently detected.

When there are blood vessel branches extracted as the target bloodvessel within the ROI determined on the basis of the first inputreceived from the user, the device for processing the blood vessel imagemay fix an upper branch of the upper branch and a lower branch adjacentto each other based on one branch point included in the ROI as a correctregion branch. The correct region branch may represent a blood vesselbranch which is not identified as the error portion or not desired to becorrected by the user in the target blood vessel extracted by the devicefor processing the blood vessel image. The device for processing theblood vessel image may identify and correct the error portion only withrespect to the lower branches based on the upper branch fixed as thecorrect region branch.

The device for processing the blood vessel image according to anotherexample embodiment may also correct the ROI determined on the basis ofthe first input received from the user according to a predeterminedcondition. For example, the predetermined condition may indicate thatthe ROI intersects at least one correct region branch which does notcorrespond to the error portion or is not desired to be corrected by theuser in the target blood vessel extracted by the device for processingthe blood vessel image in a part of the boundary of the ROI.Illustratively, the device for processing the blood vessel image canperform a correction of extending or moving the ROI so as to intersectthe at least one correct region branch which does not correspond to theerror portion or is not desired to be corrected by the user in thetarget blood vessel extracted by the device for processing the bloodvessel image in the part of the boundary of the ROI determined on thebasis of the first input received from the user. The device forprocessing the blood vessel image may correct the ROI so that thecorrect region branch among the blood vessel branches in the ROI and theROI intersect each other at an upper boundary of the ROI. However, thepresent disclosure is not limited thereto, and the ROI may be correctedto intersect the target blood vessel at any position on the boundary ofthe ROI. In addition, the device for processing the blood vessel imagemay also receive the first input from the user again when the extractedtarget blood vessel is not included in the ROI determined on the basisof the first input received from the user at all.

The device for processing the blood vessel image may identify andcorrect an error portion based on a branch point. The branch point mayindicate a point at which two or more blood vessel branches are combinedand/or a point at which the blood vessel is divided into a plurality ofblood vessel branches. A blood vessel area captured in the blood vesselimage 200 may have a plurality of branch points.

In order to finally determine the target blood vessel 210 as illustratedin FIG. 2 , the device for processing the blood vessel image accordingto an example embodiment may perform the extraction of the target bloodvessel 210, the determination of the ROI 220, and the identification andcorrection of the error portion of the extraction result within thedetermined ROI 220.

FIG. 3 illustrates an example in which an error region occurs in anextraction result of a target blood vessel according to an exampleembodiment.

The device for processing the blood vessel image according to an exampleembodiment may identify branch points and branches from the blood vesselimage. For example, the device for processing the blood vessel image mayextract a whole blood vessel area and identify the branch points and thebranches from the extracted whole blood vessel area. The device forprocessing the blood vessel image may identify blood vessel branchesbased on the branch point. The whole blood vessel area may be extractedfrom the blood vessel image. The device for processing the blood vesselimage according to an example embodiment may extract the whole bloodvessel area from the blood vessel image on the basis of a whole vesselextraction model. As described above, the whole blood vessel extractionmodel may be a model trained to generate output data indicating a resultin which the blood vessel area and the remaining non-blood vessel areaare divided from the blood vessel image.

FIG. 3 illustrates a portion 300 corresponding to the ROI 220 of theblood vessel image 200 illustrated in FIG. 2 in the extracted wholeblood vessel area. The device for processing the blood vessel image mayidentify blood vessel branches based on the branch points within the ROI220. For reference, in the present specification, an upper blood vesselbranch may indicate a branch before the branch point according to aprogress direction of a blood flow or a progress direction of thecontrast agent, and a lower blood vessel branch may indicate a branchafter the branch point. For example, as a result identified by thedevice for processing the blood vessel image, first to seventh branches301 to 307 and branch points 311 and 312 are illustrated. Based on thefirst branch point 311, the first branch 301 may be an upper bloodvessel branch, and the second branch 302 and the third branch 303 may belower blood vessel branches. In addition, a relationship between theupper blood vessel branch and the lower blood vessel branches isrelative, and may vary for each branch point. For example, the secondbranch 302 may be an upper blood vessel branch with respect to thefourth branch 304 and the fifth branch 305. The device for processingthe blood vessel image may generate blood vessel structure data bygenerating and indexing nodes corresponding to each of the blood vesselbranches. The blood vessel structure image will be described below inFIG. 9 below.

In an example illustrated in FIG. 3 , the device for processing theblood vessel image may extract the first branch 301, the third branch303, and the fifth branch 305 as blood vessel branches belonging to thetarget blood vessel. However, a blood vessel path 320 corresponding tothe target blood vessel 220 illustrated in FIG. 2 passes through thefirst branch 301, the second branch 302, and the fifth branch 305.Accordingly, in the extraction result of the exemplary target bloodvessel, the first branch point 311 directed from the first branch 301 tothe third branch 303 may be an error portion. The detection andcorrection of the error portion will be described below.

FIGS. 4 to 6 illustrate a method for identifying an error portion of theextraction result and correcting the identified error portion on thebasis of the second input received from the user within the ROI.

FIG. 4 illustrates a method for identifying and correcting adiscontinuity portion of the extraction result on the basis of thesecond input received from the user by the device for processing theblood vessel image according to an example embodiment. The device forprocessing the blood vessel image may correct an error portion on thebasis of a plurality of points of the second input, in response to acase where the second input is detected from the plurality of pointswithin the ROI.

The second input received from the user by the device for processing theblood vessel image according to an example embodiment may represent adrag input. The device for processing the blood vessel image mayidentify and correct an error portion on the basis of a movementtrajectory of a second input 491 in response to the case in which apoint at which the second input is detected moves within the ROI. Whilea point corresponding to the second input 491 moves along a regionextracted as the target blood vessel, the device for processing theblood vessel image may detect whether there is a discontinuity portionat points through which the second input 491 passes. Illustratively,when the device for processing the blood vessel image first extractsblood vessel branches 401 and 405 as a target blood vessel and the pointcorresponding to the second input 491 of the user moves along the region420 extracted as the target blood vessel, the device for processing theblood vessel image may detect whether there is a discontinuity portionat the points through which the second input 491 passes. For reference,the device for processing the blood vessel image may determine that thepoint corresponding to the second input 491 moves along the regionextracted as the target blood vessel even if the point corresponding tothe second input 491 deviates from the region extracted as the targetblood vessel for a moment. For example, the device for processing theblood vessel image may determine that the second input 491 is maintainedin the region 420 when the second input 491 moves to a point out of theaforementioned region 420 from the point other than the branch pointwithin the region 420 extracted as the target blood vessel and returnsto the region 420 again before a threshold time elapses. However, thedevice for processing the blood vessel image may determine that thesecond input 491 deviates from the region 420, in response to a casewhere the second input 491 moves to another branch out of the region 420from the branch point within the region 420 extracted as the targetblood vessel.

For example, the device for processing the blood vessel image mayreceive the second input 491 corresponding to the drag input betweengraphic points corresponding to two points included in the target bloodvessel area extracted within the ROI from the user. The drag input mayrepresent an input of clicking or touching a graphic point correspondingto one of two points included in the target blood vessel area by theuser, moving in the clicked or touched state, and releasing the click ortouch at a graphic point corresponding to the other point. The devicefor processing the blood vessel image may detect whether there is adiscontinuity portion every points between the blood vessel branchcorresponding to the start point of the second input 491 and the bloodvessel branch corresponding to the end point of the second input 491, inresponse to the second input 491 received from the user. Accordingly,the device for processing the blood vessel image may continuouslyattempt to detect the discontinuity portion while the second input 491moves along the region extracted as the target blood vessel.Illustratively, when the start point and the end point corresponding tothe second input 491 received from the user are included in the regionscorresponding to the blood vessel branches 401 and 405 and the pointcorresponding to the second input 491 moves along the region 420extracted as the target blood vessel, the device for processing theblood vessel image may detect whether there is the discontinuity portionbetween the blood vessel branches 401 and 405. When the regionscorresponding to the blood vessel branches 401 and 405 of the targetblood vessel from which the blood vessel branches 401 and 405 areextracted are separated or spaced apart from each other, the device forprocessing the blood vessel image may determine the regions as thediscontinuity portion. For example, the device for processing the bloodvessel image may determine whether the corresponding points are includedin the region 420 extracted as the target blood vessel while the secondinput 491 passes through the points between the blood vessel branches401 and 405. In response to a case where the corresponding points arenot included the region 420, the device for processing the blood vesselimage may determine the corresponding points as the discontinuityportion. According to an example embodiment, the device for processingthe blood vessel image may connect discontinued portions along themovement trajectory of the second input 491 in response to a case wherethe discontinuity portion is identified. For example, the device forprocessing the blood vessel image may connect the discontinued portionsto each other with respect to the periphery and/or boundary of the bloodvessel branches determined as the discontinuity portion. Illustratively,when the point corresponding to the second input 491 of the user movesalong the region 420 extracted as the target blood vessel, the devicefor processing the blood vessel image may connect the regionscorresponding to the blood vessel branches 401 and 405 determined as thediscontinuity portion along the movement trajectory of the second input491 received from the user. When the points corresponding to the secondinput 491 move along the region 402 between the discontinued bloodvessel branches 401 and 405, the device for processing the blood vesselimage may extract the region 402 between the discontinued blood vesselbranches 401 and 405 as the target blood vessel. That is, the device forprocessing the blood vessel image may add the region 402 to theextraction result of the target blood vessel.

The second input received from the user by the device for processing theblood vessel image according to an example embodiment may represent apointing input. The pointing input is an input indicating one point onthe display and may include, for example, a click input by mouseoperation and/or an input by touch operation to a touch display (e.g.,touch input). However, the pointing input is not limited thereto, andmay include a position indication input by various pointing devices(e.g., a trackball mouse, a touchpad, a trackpad, etc.) according to adesign. The device for processing the blood vessel image may receive apointing input for a start point and an end point as the second inputfrom the user. However, the present disclosure is not limited thereto,and the device for processing the blood vessel image may also receive apointing input of clicking or touching two or more points from the user.The device for processing the blood vessel image may identify andcorrect an error portion on the basis of a region between the startpoint and the end point of the pointing input according to the pointinginput. Illustratively, the device for processing the blood vessel imagemay first extract the blood vessel branches 401 and 405 as the targetblood vessel and detect whether there is a discontinuity portion in ablood vessel area between points 492 and 493 corresponding to the secondinput of the user.

For example, the device for processing the blood vessel image mayreceive the second input corresponding to the pointing input includingthe click or touch input for the two points 492 and 493 included in thetarget blood vessel area extracted within the ROI from the user. Thedevice for processing the blood vessel image may detect whether there isthe discontinuity portion every points between the blood vessel branchcorresponding to the start point 492 of the second input and the bloodvessel branch corresponding to the end point of the second input inresponse to the second input received from the user and correct thediscontinuity portion in the same manner as the case of receiving thedrag input as the second input.

FIG. 5 illustrates a method for identifying and correcting amisidentification portion of the extraction result on the basis of themovement trajectory of the input received from the user by the devicefor processing the blood vessel image according to an exampleembodiment. The device for processing the blood vessel image maydetermine a blood vessel branch located out of the region correspondingto the movement trajectory of the second input among the blood vesselbranches extracted as the target blood vessel connected with the branchpoint as the misidentification portion, in response to a case where thepoint corresponding to a second input 590 moves from the branch pointwithin the area extracted as the target blood vessel to an area out ofthe target blood vessel. When the device for processing the blood vesselimage determines the portion related to the branch point as themisidentification portion, the ROI on the basis of the first input maybe extended so that all the lower branches based on the branch point areincluded within the ROI. Illustratively, the device for processing theblood vessel image may first extract blood vessel branches 501, 502, and505 as the target blood vessel and determine a portion related to abranch point 513 as the misidentification portion, when the pointcorresponding to the second input 590 of the user moves to a region 530out of the target blood vessel from the branch point 513 within theregion 520 extracted as the target blood vessel. For example, when thesecond input 590 moves to the region corresponding to the lower bloodvessel branch 504 different from the lower blood vessel branch 505 firstextracted as the target blood vessel based on the branch point 513, thedevice for processing the blood vessel image may determine that thepoint corresponding to the second input 590 received from the user movesto the region out of the target blood vessel. The device for processingthe blood vessel image may determine at least one branch 505 of theblood vessel branches extracted as the target blood vessel adjacent tothe branch point 513 as the misidentification portion in the extractionresult for the target blood vessel.

The device for processing the blood vessel image may replace at leastone of the blood vessel branches identified as the misidentificationportion with a blood vessel branch indicated by the second input 590 outof the target blood vessel and correct the remaining extraction resultson the basis of the replaced blood vessel branch. For example, when thepoints corresponding to the second input 590 move out of the regioncorresponding to the extracted target blood vessel, the device forprocessing the blood vessel image may replace the lower blood vesselbranch 505 first extracted as the target blood vessel based on thebranch point 513 with the blood vessel branch 504. The device forprocessing the blood vessel image may correct the extraction result ofthe target blood vessel on the basis of the replaced blood vessel branch504. For example, the device for processing the blood vessel image mayexclude blood vessel branches subsequent to the lower blood vesselbranch 505 first extracted from the extraction result of the targetblood vessel and add the blood vessel branches subsequent to thereplaced blood vessel branch 504 to the extraction result of the targetblood vessel.

FIG. 6 illustrates a method for providing correction candidates to theuser on the basis of a second input 690 received from the user andidentifying and correcting an error portion according to a selectioninput of the user. When the second input 690 is detected for a firstthreshold time or more at the point in the region corresponding to theextraction result of the target blood vessel, the device for processingthe blood vessel image may determine the corresponding point as theerror portion. The device for processing the blood vessel image mayprovide correction candidates corresponding to the point determined asthe error portion to the user. The correction candidates may represent aset of candidate blood vessel branches having a shape capable ofreplenishing the discontinuity portion or a set of candidate bloodvessel branches having a shape and a structure capable of replacing themisidentification portion, when the point where the second input 690 ismaintained is determined as the error portion. For example, the devicefor processing the blood vessel image may determine the correctioncandidates on the basis of blood vessel structure data, curvatureinformation of the blood vessel, diameter information of the bloodvessel, brightness information of the blood vessel, and the likeaccording to those illustrated in FIGS. 7 to 14 below. For example, afirst correction candidate 661 may be a candidate branch determined onthe basis of the blood vessel structure data, a second correctioncandidate 662 may be a candidate branch determined on the basis of thecurvature information, a third correction candidate 663 may be acandidate branch determined on the basis of the diameter information,and a fourth correction candidate 664 may be a candidate branchdetermined on the basis of the brightness information. However, this isonly illustrative, and the determination of the candidate branches mayvary depending on a design. In addition, although the example ofdetermining the point where the second input 690 is maintained as theerror portion has been described above, the device for processing theblood vessel image may also determine the error portion on the basis ofthe blood vessel structure data, the curvature information of the bloodvessel, the diameter information of the blood vessel, the brightnessinformation of the blood vessel, and the like according to thoseillustrated below in FIGS. 7 to 14 with respect to the point where thesecond input 690 is maintained.

The device for processing the blood vessel image may select one of thecorrection candidates on the basis of a third input for selecting thecorrection candidates received from the user. The device for processingthe blood vessel image may add blood vessel branches included in theselected correction candidates to the extraction result of the targetblood vessel.

Illustratively, the device for processing the blood vessel image mayfirst extract blood vessel branches 601, 602, and 605 as the targetblood vessel. When the point where the second input 690 received fromthe user is detected is included in the region corresponding to a branchpoint 611, the device for processing the blood vessel image may output agraphic object 660 capable of providing the user with the selection forone of the correction candidates 661, 662, 663, and 664 corresponding tothe branch point 611. The device for processing the blood vessel imagemay receive the third input selecting one of the correction candidates661, 662, 663, and 664 from the user to extract the blood vesselbranches (e.g., the blood vessel branches 602 and 604) consisting of theselected correction candidate as the target blood vessel.

When the point corresponding to the second input 690 is a pointcorresponding to a boundary (e.g., a blood vessel edge) of the extractedtarget blood vessel and the time when the second input 690 is detectedat the corresponding point is a second threshold or more, the device forprocessing the blood vessel image may provide the user with correctioncandidates corresponding to the boundary. For example, the device forprocessing the blood vessel image may provide the user with an option ofa correction candidate of smoothing softly the boundary, a correctioncandidate of emphasizing a contrast with a background, or a correctioncandidate of selecting a boundary different from the existing boundary,with respect to the boundary of the target blood vessel corresponding tothe second input 690 received from the user.

The device for processing the blood vessel image may identify an errorportion from the extraction result of the target blood vessel andcorrect the identified error portion in response to the determination ofthe ROI. The device for processing the blood vessel image may providethe user with the correction result of the error portion. The device forprocessing the blood vessel image may provide the user with thecorrection result of the error portion to correct the error portion byreceiving the input corresponding to the correction result from the userand identify and correct the error portion on the basis of the secondinput 690 received from the user within the ROI in which the errorportion is corrected. In other words, the device for processing theblood vessel image may perform a preprocessing process of providing thecorrection result to the user by identifying and correcting the errorportion automatically by the processor, before the error portion isidentified and corrected by receiving the second input 690 from the userwithin the ROI.

For reference, in FIGS. 4 to 6 , the second inputs 491, 590, and 690 areillustrated as the touch input for convenience of description, but arenot limited thereto, and may also include other types of inputs forpointing the points on the display, such as a click input.

FIGS. 7 and 8 illustrate a method for correcting an error portionaccording to an example embodiment.

FIG. 7 illustrates a method for providing the user with a correctionresult of a misidentification portion when an error portion isidentified from the extraction result of the target blood vessel and theidentified error portion is the misidentification portion. According toan example embodiment, the device for processing the blood vessel imagemay correct the identified error portion on the basis of a user input(e.g., a touch input) when the error portion is identified in the targetblood vessel. The device for processing the blood vessel image mayprovide one or more candidate branches to the user in response to a casewhere the error portion is the misidentification portion. In response toa case of receiving a pointing input for one branch among one or morecandidate branches from the user, the device for processing the bloodvessel image may replace a branch corresponding to the error portionwith the selected branch. Illustratively, when the device for processingthe blood vessel image first extracts blood vessel branches 701 and 702as a target blood vessel, the device for processing the blood vesselimage may determine at least one branch of the blood vessel branches 701and 702 as an error portion in the extraction result for the targetblood vessel on the basis of at least one of blood vessel structure datarelated to the target blood vessel, curvature information of the targetblood vessel, diameter information of the target blood vessel, andbrightness information of the target blood vessel. The device forprocessing the blood vessel image may provide the user with one or morecandidate blood vessel branches 711, 712, and 713 which are notextracted as the target blood vessel, when the identified error portionis the misidentification portion. An input/output interface of thedevice for processing the blood vessel image may output graphic objects771, 772, and 773 that can provide the user with a selection of thecandidate blood vessel branches 711, 712, and 713 through a display. Thegraphic objects may have a shape surrounding regions corresponding tothe candidate blood vessel branches. In FIG. 7 , the graphic objects771, 772, and 773 are illustrated in a rectangular shape, but the shapeis not limited thereto. The user may select a candidate blood vesselbranch through a pointing input of simply clicking or touching a pointcorresponding to one of the graphic objects corresponding to thecandidate blood vessel branches output on the display. That is, when thedevice for processing the blood vessel image detects a user input withrespect to a point corresponding to the graphic object, the device forprocessing the blood vessel image may determine that a candidate bloodvessel branch corresponding to the graphic object is selected, and mayreplace the blood vessel branch corresponding to the error portion witha selected candidate blood vessel branch. Illustratively, when thedevice for processing the blood vessel image detects the user input fora point corresponding to the graphic object 771 from the user, thedevice for processing the blood vessel image may extract the candidateblood vessel branch 711 corresponding to the graphic object 771 as thetarget blood vessel. That is, the device for processing the blood vesselimage may replace the blood vessel branch 702 with the blood vesselbranch 711 in the extraction result of the target blood vessel.

FIG. 8 illustrates a method for providing the user with a correctionresult of a discontinuity portion when an error portion is identifiedfrom the extraction result of the target blood vessel and the identifiederror portion is the discontinuity portion. The device for processingthe blood vessel image according to an example embodiment may provide ablood vessel area including the discontinuity portion to the user inresponse to a case where the error portion identified in the targetblood vessel is the discontinuity portion. The device for processing theblood vessel image may connect a region corresponding to a blood vesselbranch corresponding to a start point of the user input and a regioncorresponding to a blood vessel branch corresponding to an end point ofthe user input, in response to a case where the user input is detectedin a plurality of points with respect to a correction result.

In response to a drag input 891 received from the user with respect tothe correction result, the device for processing the blood vessel imageaccording to an example embodiment may connect a region corresponding toa blood vessel branch corresponding to a start point of the drag input891 and a region corresponding to a blood vessel branch corresponding toan end point of the drag input 891. Illustratively, when the device forprocessing the blood vessel image first extracts blood vessel branches801 and 802 as a target blood vessel, the device for processing theblood vessel image may determine regions corresponding to the bloodvessel branches 801 and 802 of the extracted target blood vessel asdiscontinuity portions separated from each other. The input/outputinterface of the device for processing the blood vessel image may outputa graphic object 870 related to the connection between the regionscorresponding to the blood vessel branches 801 and 802 through adisplay. The graphic object 870 has a shape enclosing the regioncorresponding to at least a portion of the blood vessel branches 801 and802 corresponding to the discontinuity portions and may represent thatthe blood vessel branches 801 and 802 are connectable by the user. Thedevice for processing the blood vessel image may connect the regionscorresponding to the blood vessel branches 801 and 802 selected by thedrag input 891 and extract a blood vessel branch 803 between thediscontinued blood vessel branches 801 and 802 as the target bloodvessel, in response to the drag input 891 received from the user. Thebranches selected by the drag input 891 may indicate a blood vesselbranch corresponding to a drag start point and a blood vessel branchcorresponding to a drag end point. That is, the device for processingthe blood vessel image may include the blood vessel branch 803 in theextraction result of the target blood vessel.

The device for processing the blood vessel image according to anotherexample embodiment may connect regions corresponding to blood vesselbranches corresponding to a start point 892 and an end point 893 of apointing input, in response to the pointing input corresponding to twoor more points received from the user with respect to the correctionresult. That is, the device for processing the blood vessel image mayreceive a click or touch input for the start point and the end pointfrom the user. In response to the pointing input received from the user,the device for processing the blood vessel image may connect a regioncorresponding to the blood vessel branch 801 corresponding to the startpoint 892 of the pointing input and a region corresponding to the bloodvessel branch 802 corresponding to the end point 893 of the pointinginput.

FIG. 9 illustrates a method of identifying an error in a target bloodvessel using a topology of blood vessel structure data based on nodescorresponding to blood vessel branches.

According to an example embodiment, the device for processing the bloodvessel image may identify an error portion on the basis of blood vesselstructure data 900 related to the target blood vessel. The blood vesselstructure data 900 is topological data indicating the structure of ablood vessel, and may be, for example, tree structure data in whichnodes corresponding to blood vessel branches are indexed. For example,the device for processing the blood vessel image may identify bloodvessel branches based on blood vessel branch points with respect to thewhole blood vessel area, generate nodes corresponding to each of theidentified blood vessel branches, and generate the blood vesselstructure data 900 on the basis of the indexing of the generated nodes.

When the upper blood vessel branch is branched to a plurality of lowerblood vessel branches based on the branch point, the device forprocessing the blood vessel image may connect a node corresponding tothe upper blood vessel branch and nodes corresponding to the lower bloodvessel branches. The device for processing the blood vessel image maygenerate the blood vessel structure data 900 for the whole blood vesselsby repeating the connection of the nodes to the branch points and thevessel blood branches identified from the blood vessel image. Forexample, in the blood vessel structure data 900 illustrated in FIG. 9 ,first to seventh nodes N1 to N7 may sequentially correspond to the firstto seventh branches 301 to 307 illustrated in FIG. 3 , respectively. Thefirst node N1 may be an uppermost node, and the second node N2 and thethird node N3 may be lower nodes of the first node N1. The remainingnodes may have similar top-down relationships.

The device for processing the blood vessel image according to an exampleembodiment may calculate node connection data 910 between the nodescorresponding to the blood vessel branches extracted as the target bloodvessel from the blood vessel image. For example, the device forprocessing the blood vessel image may calculate the node connection data910 connected with the first node N1, the third node N3, and the fifthnode N5 from the extraction result of the target blood vesselillustrated in FIG. 3 .

The device for processing the blood vessel image may identify an errorportion of the target blood vessel by comparing the node connection data910 with the blood vessel structure data 900. The device for processingthe blood vessel image may detect a connection error between the nodesof the target blood vessel on the basis of the generated blood vesselstructure data 900. The device for processing the blood vessel image maydetermine, as an error portion, blood vessel branches and/or branchpoints corresponding to the nodes in which the connection error isdetected. The device for processing the blood vessel image may determinean error portion on the basis of nodes which are not matched with theblood vessel structure data 900 in the node connection data 910.Illustratively, the node connection data 910 extracted in FIG. 9 mayindicate that the first node N1, the third node N3, and the fifth nodeN5 are sequentially connected. In the blood vessel structure data 900,the third node N3 is not connected to the fifth node N5. In other words,the device for processing the blood vessel image may determine that theconnection between the third node N3 and the fifth node N5 in the nodeconnection data 910 does not match the blood vessel structure data 900.The connection between the third node N3 and the fifth node N5 may be aconnection error. The device for processing the blood vessel image maydetermine a blood vessel branch corresponding to at least one node ofthe nodes corresponding to the connection error as the error portion.For example, in FIG. 9 , the device for processing the blood vesselimage may determine a blood vessel branch corresponding to at least oneof the third node N3 and the fifth node N5 as the error portion. In theabove-described example, since the blood vessel branch corresponding tothe third node N3 or the fifth node N5 is erroneously extracted as thetarget blood vessel, the blood vessel branch may be a misidentificationportion.

As another example, the device for processing the blood vessel image maydetect the blood vessel branch corresponding to a node missing from thenode connection data 920 as a discontinuity portion on the basis of theblood vessel structure data 900. The device for processing the bloodvessel image may calculate the node connection data 920 directlyconnected from the first node N1 to the fifth node N5. The device forprocessing the blood vessel image may detect that the second node N2 ismissing from the node connection data 920 on the basis of the bloodvessel structure data 900. In this case, the device for processing theblood vessel image may detect a blood vessel branch corresponding to thesecond node N2 as the discontinuity portion.

FIGS. 10 and 11 illustrate a method for correcting an error portionaccording to an example embodiment.

FIG. 10 illustrates a correction in the case where the node connectiondata 910 is calculated in FIG. 9 . According to an example embodiment,in response to a case where the misidentification portion is identified,the device for processing the blood vessel image may replace a nodecorresponding to the misidentification portion with a node matching theblood vessel structure data. Illustratively, the device for processingthe blood vessel image may determine that the fifth node N5 does notmatch the blood vessel structure data in the node connection data 910.The device for processing the blood vessel image may exclude the fifthnode N5 that does not match the blood vessel structure data from thenode connection data and add the sixth node N6 matching the blood vesselstructure data to the node connection data to generate corrected nodeconnection data 1010. Accordingly, the device for processing the bloodvessel image may extract a blood vessel branch (e.g., a sixth branch 306in FIG. 6 ) corresponding to the replaced sixth node N6 as the targetblood vessel.

FIG. 11 illustrates a correction in the case where the node connectiondata 920 is calculated in FIG. 9 . According to an example embodiment,the device for processing the blood vessel image may insert aconnectable node between the nodes corresponding to the discontinuityportion in response to a case where the discontinuity portion isidentified. Illustratively, the device for processing the blood vesselimage may determine that a space between the first node N1 and the fifthnode N5 is missing from the node connection data 920. The device forprocessing the blood vessel image may generate corrected node connectiondata 1110 by inserting the second node N2 between the nodes N1 and N5.The device for processing the blood vessel image may extract a bloodvessel branch (e.g., the second branch 302 in FIG. 3 ) corresponding tothe second node N2 as the target blood vessel.

As described above, by correcting the misidentification portion byreplacing the nodes and adding the nodes, the device for processing theblood vessel image may remove a node connectivity error on the basis ofa topology of the blood vessel structure data.

FIG. 12 illustrates a method for identifying and correcting an error ina target blood vessel using curvature information of the target bloodvessel.

According to an example embodiment, the device for processing the bloodvessel image may identify and correct a misidentification portion byusing a curvature between blood vessel branches adjacent to each otherin the target blood vessel. For example, the device for processing theblood vessel image may determine branches adjacent to each other as amisidentification portion in response to a case where a curvaturebetween the branches adjacent to each other in the target blood vesselexceeds a threshold curvature. Illustratively, when the device forprocessing the blood vessel image first extracts blood vessel branches1201 and 1202 as a target blood vessel, the device for processing theblood vessel image may calculate a curvature between the blood vesselbranches 1201 and 1202. The device for processing the blood vessel imagemay determine at least one branch of the above-described blood vesselbranches 1201 and 1202 as the misidentification portion in theextraction result for the target blood vessel in response to a casewhere the calculated curvature exceeds the threshold curvature. Theblood vessel branches adjacent to each other in the target blood vesselto be actually extracted from the blood vessel image have a relativelysmall curvature. Accordingly, there is a possibility that the bloodvessel branches adjacent to each other having a curvature exceeding thethreshold curvature may be the error portion.

The device for processing the blood vessel image may correct theidentified error portion, in response to a case where the error portionis identified in the target blood vessel using the threshold curvature.The device for processing the blood vessel image may replace one branchof the branches adjacent to each other with a candidate branch having acurvature with the remaining branches of the threshold curvature orless, with respect to the identified error portion. The candidate branchmay represent one or more remaining branches that are not extracted asthe target blood vessel among a plurality of blood vessel branchesconnected to one blood vessel branch based on an arbitrary branch point.Illustratively, when the curvature between the upper blood vessel branch1201 and the blood vessel branch 1203 which is not extracted as thetarget blood vessel is the threshold curvature or less, the device forprocessing the blood vessel image may extract the blood vessel branch1203 instead of the blood vessel branch 1202 as the target blood vessel.The device for processing the blood vessel image may replace the bloodvessel branch 1202 with the blood vessel branch 1203 in the extractionresult of the target blood vessel. Furthermore, when correcting theidentified error portion, the device for processing the blood vesselimage may apply a different threshold curvature according to a type ofblood vessel (e.g., left main coronary artery (LM), left anteriordescending artery (LAD), left circumflex artery (LCX), and rightcoronary artery (RCA)) or a blood vessel area (e.g., proximal region,mid region, and distal region).

The device for processing the blood vessel image may perform principaldirection component analysis (e.g., principal component analysis (PCA))of a blood vessel branch in order to analyze a difference in curvature.The device for processing the blood vessel image may analyze a principaldirection component for each of the blood vessel branches divided basedon the branch point. The principal direction component of the bloodvessel branch may represent a component representing a direction of thecorresponding blood vessel branch. For example, the device forprocessing the blood vessel image may obtain a principal directionvector for each of the blood vessel branches by using the principaldirection component analysis for each of the blood vessel branches. Theprincipal direction vector is a vector having a direction componentrepresenting a direction in which the blood vessel branch extends fromthe branch point, and may have a size of a unit vector. For example, theprincipal direction vector for any blood vessel branch may indicate adirection of the principal components of vector components directed fromthe branch point to points corresponding to the blood vessel branch. Forexample, the principal direction vectors of the blood vessel branches1201, 1202, and 1203 may correspond to vectors 1221, 1222, and 1223,respectively. The device for processing the blood vessel image maydetermine branches adjacent to each other as a misidentificationportion, in response to a case where inner product values of theprincipal direction vectors of the blood vessel branches adjacent toeach other in the target blood vessel exceed a threshold value.

Illustratively, when inner product values of the principal directionvectors 1221 and 1222 of the blood vessel branches 1201 and 1202adjacent to each other exceed the threshold value in the target bloodvessel, the device for processing the blood vessel image may determinethe blood vessel branches 1201 and 1202 adjacent to each other as themisidentification portion. Since the principal direction vector of eachof the blood vessel branches has the size of a unit vector, the innerproduct values of the principal direction vectors may depend on anglesbetween the vectors. As a result, since the principal direction vectorcorresponding to the upper branch and the principal direction vectorcorresponding to the lower branch are directed in opposite directions,the inner product of the two principal direction vectors has a negativevalue. Accordingly, when the inner product values of the principaldirection vectors are a threshold value or more, it may be meant thatthe curvature between the blood vessel branches is large. The targetblood vessel to be actually extracted from the blood vessel image is oneblood vessel and has generally no large curvature change between theblood vessel branches adjacent to each other. Accordingly, when theinner product value of the principal direction vector between the bloodvessel branches adjacent to each other exceeds the threshold value, thedevice for processing the blood vessel image may extract blood vesselsother than the target blood vessel to be actually found. Furthermore, inthe correcting of the identified error portion, the device forprocessing the blood vessel image may apply different threshold valuesaccording to a type of blood vessel or a blood vessel area.

The device for processing the blood vessel image may obtain a principaldirection vector for each blood vessel branch segmented based on thebranch point with respect to the extracted target blood vessel, but mayalso obtain a principal direction vector for each piece segmented in apredetermined length by segmenting the blood vessel in the predeterminedlength. The device for processing the blood vessel image may alsoidentify an error portion in the target blood vessel by comparingprincipal directions of adjacent pieces with respect to the extractedtarget blood vessel to find a portion in which the curvature is greaterthan or equal to a threshold value. In other words, the device forprocessing the blood vessel image may segment the extracted target bloodvessel in a threshold length or less. The device for processing theblood vessel image may determine pieces adjacent to each other as themisidentification portion, in response to a case where inner productvalues of the principal direction vectors of the pieces adjacent to eachother segmented in the predetermined length exceed the threshold value.Since the device for processing the blood vessel image may calculate acurvature between the adjacent pieces by segmenting the target bloodvessel in a threshold length or less, the device for processing theblood vessel image may identify the error portion of the target bloodvessel more accurately than a case of identifying the error portion ofthe target blood vessel according to the blood vessel branches segmentedbased on the branch point.

The device for processing the blood vessel image may correct theidentified error portion in response to a case where the error portionis identified in the target blood vessel using the principal directionvector. The device for processing the blood vessel image may replace onebranch of the branches adjacent to each other with a candidate branchhaving an inner product value of the principal direction vector with theremaining branches of the threshold value or less, with respect to theidentified error portion. Illustratively, when the inner product valueof principal direction vectors 1223 and 1221 between the upper bloodvessel branch 1201 and the blood vessel branch 1203 which is notextracted as the target blood vessel is the threshold value or less, thedevice for processing the blood vessel image may extract the bloodvessel branch 1203 instead of the blood vessel branch 1202 as the targetblood vessel. The device for processing the blood vessel image mayreplace the blood vessel branch 1202 with the blood vessel branch 1203in the extraction result of the target blood vessel.

FIG. 13 illustrates a method for identifying and correcting an error ina target blood vessel using diameter information of the target bloodvessel.

According to an example embodiment, the device for processing the bloodvessel image may identify and correct a misidentification portion bycalculating a diameter difference between the blood vessel branchesadjacent to each other in the target blood vessel. For example, thedevice for processing the blood vessel image may determine branchesadjacent to each other as the misidentification portion in response to acase where a diameter difference between the blood vessel branchesadjacent to each other in the target blood vessel is a thresholddiameter difference or more. The device for processing the blood vesselimage may acquire diameter information with respect to each of the bloodvessel branches identified based on the branch points. For example,diameters of blood vessel branches 1301, 1302, and 1303 illustrated inFIG. 13 may correspond to r1, r2, and r3, respectively. Illustratively,when the device for processing the blood vessel image first extracts theblood vessel branches 1301 and 1302 as a target blood vessel, the devicefor processing the blood vessel image may calculate a diameterdifference between the blood vessel branches 1301 and 1302. The devicefor processing the blood vessel image may determine at least one branchof the above-described blood vessel branches 1301 and 1302 as themisidentification portion in the extraction result for the target bloodvessel in response to a case where the calculated diameter difference isa threshold diameter difference or more. The blood vessel branchesadjacent to each other in the target blood vessel to be actuallyextracted from the blood vessel image have relatively small diameterdifference. Accordingly, there is a possibility that the adjacent bloodvessel branches having a diameter difference of the threshold diameterdifference or more may be the error portion.

The device for processing the blood vessel image may calculate adiameter difference between the blood vessel branches adjacent to eachother with respect to the extracted target blood vessel, but maycalculate a diameter difference by smoothing the diameter information ofthe blood vessel branches. It is general to represent a relatively smallchange in diameter between the blood vessel branches adjacent to eachother in the target blood vessel to be actually extracted from the bloodvessel image. However, when the target blood vessel to be extractedincludes a blood vessel branch having a disease, a large change indiameter may occur between blood vessel branches adjacent to the bloodvessel branch having the disease. Accordingly, the device for processingthe blood vessel image may identify a misidentification portion in theextracted target blood vessel by smoothing the diameter information ofblood vessel branches by binding the plurality of blood vessel branchesto calculate a diameter difference.

The device for processing the blood vessel image may correct theidentified error portion in response to a case where the error portionis identified in the target blood vessel using the diameter information.The device for processing the blood vessel image may replace one branchof the branches adjacent to each other with a candidate branch having adiameter difference from the remaining branches of less than thethreshold diameter difference, with respect to the identifiedmisidentification portion. Illustratively, when the diameter differencebetween the blood vessel branch 1301 and the blood vessel branch 1303which is not extracted as the target blood vessel is less than thethreshold diameter difference, the device for processing the bloodvessel image may extract the blood vessel branch 1303 instead of theblood vessel branch 1302 as the target blood vessel. The device forprocessing the blood vessel image may replace the blood vessel branch1302 with the blood vessel branch 1303 in the extraction result of thetarget blood vessel. Furthermore, when correcting the identified errorportion, the device for processing the blood vessel image may apply adifferent threshold diameter difference according to a type of bloodvessel (e.g., LM, LAD, LCX, and RCA) or a blood vessel area.

FIG. 14 illustrates a method for identifying and correcting an error ina target blood vessel using brightness information of the target bloodvessel.

According to an example embodiment, the device for processing the bloodvessel image may identify and correct a misidentification portion bycalculating a brightness difference between blood vessel branchesadjacent to each other in the target blood vessel. For example, thedevice for processing the blood vessel image may determine branchesadjacent to each other as the misidentification portion, in response toa case where a brightness difference between the branches adjacent toeach other in the target blood vessel is a threshold brightnessdifference or more. The device for processing the blood vessel image mayacquire brightness information with respect to each of the blood vesselbranches identified based on the branch points. For example, thebrightness of the blood vessel branches may indicate a distributionconcentration of a contrast agent injected to obtain a blood vesselimage. Illustratively, when the device for processing the blood vesselimage first extracts blood vessel branches 1401 and 1402 as a targetblood vessel, the device for processing the blood vessel image maycalculate a brightness difference between the blood vessel branches 1401and 1402. The device for processing the blood vessel image may determineat least one branch of the above-described blood vessel branches 1401and 1402 as the misidentification portion in the extraction result forthe target blood vessel in response to a case where the calculatedbrightness difference is the threshold brightness difference or more.The adjacent blood vessel branches in the target blood vessel to beactually extracted from the blood vessel image have a relatively smallchange in brightness. Accordingly, there is a possibility that theadjacent blood vessel branches having a brightness difference of thethreshold brightness difference or more may be the error portion.

The device for processing the blood vessel image may correct theidentified error portion, in response to a case where the error portionis identified in the target blood vessel using the brightnessinformation. The device for processing the blood vessel image mayreplace one branch of the branches adjacent to each other with acandidate branch having a brightness difference from the remainingbranches of less than the threshold brightness difference, with respectto the identified misidentification portion. Illustratively, when thebrightness difference between the blood vessel branch 1401 and the bloodvessel branch 1403 which is not extracted as the target blood vessel isless than the threshold brightness difference, the device for processingthe blood vessel image may extract the blood vessel branch 1403 insteadof the blood vessel branch 1402 as the target blood vessel. The devicefor processing the blood vessel image may replace the blood vesselbranch 1402 with the blood vessel branch 1403 in the extraction resultof the target blood vessel. Furthermore, when correcting the identifiederror portion, the device for processing the blood vessel image mayapply a different threshold brightness difference according to a type ofblood vessel (e.g., LM, LAD, LCX, and RCA) or a blood vessel area. As aresult, the device for processing the blood vessel image may perform apreprocessing portion of identifying the error portion of the targetblood vessel first extracted by the method of FIGS. 8 to 14 , andproviding the correction result of the identified error portion to theuser.

The device for processing the blood vessel image according to an exampleembodiment may generate a new extraction result for the target bloodvessel based on the model ensemble distinguished from the model ensembleapplied in the previous extraction result, in response to a case wherethe error portion is identified. When the error portion is identified,the device for processing the blood vessel image may generate a newextraction result for the target blood vessel based on one modelensemble distinguished from the model ensemble applied in the previousextraction result among a plurality of stored machine learning modelswithout directly correcting the error portion.

In addition, the device for processing the blood vessel image maygenerate a plurality of new extraction results for the target bloodvessel with respect to each of a plurality of model ensembles on thebasis of the model ensembles distinguished from the model ensembleapplied in the previous extraction result among the plurality of storedmachine learning models. The device for processing the blood vesselimage may identify an error portion every extraction result of thetarget blood vessel generated according to the model ensemble on thebasis of at least one of blood vessel structure data related to thetarget blood vessel, curvature information of the target blood vessel,diameter information of the target blood vessel, and brightnessinformation of the target blood vessel. The device for processing theblood vessel image may automatically select one extraction resultclosest to the target blood vessel to be actually extracted amonggenerated extraction results for the plurality of target blood vesselsas a target blood vessel to provide the selected extraction result tothe user. For example, the device for processing the blood vessel imagemay select an extraction result for a target blood vessel with thesmallest identified error portion as the extraction result closest tothe target blood vessel to be actually extracted, but is not limitedthereto. The device for processing the blood vessel image may extractthe selected extraction result as the target blood vessel in response tothe selection input of the user. Furthermore, the device for processingthe blood vessel image may provide information on the extraction resultsfor the plurality of target blood vessels to the user. The device forprocessing the blood vessel image may receive one of the extractionresults for the plurality of target blood vessels from the user toextract one extraction result indicated by the input as the target bloodvessel. Accordingly, the device for processing the blood vessel imagemay perform a preprocessing process of providing the user with thecorrection result of the target blood vessel using a different machinelearning model.

The device for processing the blood vessel image according to an exampleembodiment may extract one blood vessel branch of candidate blood vesselbranches as the target blood vessel on the basis of a connectivity scorefor each of the candidate blood vessel branches in response to a casewhere the error portion is identified in the extraction result of thetarget blood vessel. When the error portion is identified in theextraction result of the target blood vessel, the device for processingthe blood vessel image may select one blood vessel branch of thecandidate blood vessel branches capable of correcting the error portion.The device for processing the blood vessel image may calculate aconnectivity score for each of the candidate blood vessel branches. Theconnectivity score is a score indicating the connectivity between ablood vessel branch adjacent to any candidate blood vessel branch andthe corresponding candidate blood vessel branch in the extraction resultof the target blood vessel. The connectivity score may be calculated onthe basis of a degree of matching, a curvature difference, a diameterdifference, a brightness difference, etc. for blood vessel structuredata between the candidate blood vessel branch and the adjacent bloodvessel branch. The connectivity score may correspond to a degree similarto the target blood vessel to be actually extracted from the correctedtarget blood vessel when the candidate blood vessel branch is includedas the target blood vessel.

For example, when the candidate blood vessel branch is extracted as thetarget blood vessel, the device for processing the blood vessel imagemay calculate a connectivity score between the candidate blood vesselbranch and the blood vessel branches adjacent and connected to thecandidate blood vessel branch on the basis of at least one of the bloodvessel structure data related to the target blood vessel, the curvatureinformation of the target blood vessel, the diameter information of thetarget blood vessel, and the brightness information of the target bloodvessel. However, the present disclosure is not limited thereto, and theconnectivity score for each of the candidate blood vessel branches maybe calculated using various methods. The device for processing the bloodvessel image may select one blood vessel branch of the candidate bloodvessel branches on the basis of the connectivity score. For example, asa blood vessel branch having the highest connectivity score among thecandidate blood vessel branches, a blood vessel branch determined tohave the smallest error may be selected. The device for processing theblood vessel image may extract the selected blood vessel branch as thetarget blood vessel.

Illustratively, in FIG. 9 , the device for processing the blood vesselimage calculates the node connection data 910 to which the first nodeN1, the third node N3, and the fifth node N5 are connected from theextraction result of the target blood vessel, the device for processingthe blood vessel image may determine that the connection between thethird node N3 and the fifth node N5 in the node connection data 910 doesnot match the blood vessel structure data 900. The device for processingthe blood vessel image may determine a blood vessel branch correspondingto at least one node of the nodes N3 and N5 corresponding to theconnection error as the error portion. When the device for processingthe blood vessel image determines the blood vessel branch correspondingto the third node N3 as the error, the device for processing the bloodvessel image may exclude the third node N3 which does not match theblood vessel structure data from the node connection data and add thesecond node N2 matching the blood vessel structure data to the nodeconnection data. In addition, when the device for processing the bloodvessel image determines the blood vessel branch corresponding to thefifth node N5 as the error, the device for processing the blood vesselimage may exclude the fifth node N5 which does not match the bloodvessel structure data from the node connection data and add a sixth nodeN6 or a seventh node N7 matching the blood vessel structure data to thenode connection data. As a result, the device for processing the bloodvessel image may calculate a connectivity score for each of candidateblood vessel branches corresponding to the second node, the sixth node,and the seventh node that may be nodes of the target blood vessel. Thedevice for processing the blood vessel image may select a blood vesselbranch determined to have the smallest error to extract the selectedblood vessel branch as the target blood vessel, on the basis of theconnectivity score for each of the candidate blood vessel branches.

As another example, in FIG. 12 , when the device for processing theblood vessel image first extracts the blood vessel branches 1201 and1202 as the target blood vessel, the device for processing the bloodvessel image may determine the blood vessel branches as an error portionwhen a curvature between the blood vessel branches 1201 and 1202 exceedsa threshold curvature. The device for processing the blood vessel imagemay replace one branch of the branches adjacent to each other with acandidate branch having a curvature with the remaining branches of thethreshold curvature or less. Unlike illustrated in FIG. 12 , when thereis a plurality of candidate blood vessel branches, the device forprocessing the blood vessel image may calculate a connectivity score foreach of the candidate blood vessel branches. The device for processingthe blood vessel image may select a blood vessel branch determined tohave the smallest error to extract the selected blood vessel branch asthe target blood vessel, on the basis of the connectivity score for eachof the candidate blood vessel branches. Even in FIGS. 13 and 14 , thedevice for processing the blood vessel image may select and extract oneof the candidate blood vessel branches as the target blood vessel in thesame manner as described above.

FIG. 15 is a block diagram schematically illustrating a device forprocessing a blood vessel image according to an example embodiment.

A system 1500 for processing a blood vessel image according to anexample embodiment may include a blood vessel image processing device1510 and a blood vessel image photographing device 1520. The bloodvessel image processing device 1510 may include an image receiver 1511,a processor 1512, and an input/output interface 1513.

The image receiver 1511 may receive a blood vessel image photographed bythe blood vessel image photographing device 1520. The image receiver1511 may receive the blood vessel image from the blood vessel imagephotographing device 1520 through wired/wireless data communication.However, the present disclosure is not limited thereto, and the bloodvessel image photographing device 1520 may also be configured to beintegrated into the image receiver 1511.

The processor 1512 may extract the target blood vessel from the bloodvessel image received from the image receiver using a machine learningmodel, determine an ROI for the extraction result of the target bloodvessel on the basis of the first input received from the user, identifyan error portion of the extraction result on the basis of the secondinput received from the user within the determined ROI, and correct theidentified error portion. The operation of the processor 1512 is notlimited thereto, and the processor 1512 may perform the operationsdescribed above with reference to FIGS. 1 to 14 .

The input/output interface 1513 may receive the input from the user totransmit the received input to the processor. For example, theinput/output interface 1513 may receive the input according to a mouseoperation, a touch operation, and the like. In addition, theinput/output interface 1513 may provide visual feedback to the user. Forexample, the input/output interface 1513 may output the extractionresult of the target blood vessel through the display step by step.

The national R&D projects supporting the present disclosure are asfollows.

[Project Unique Number] 1415166912

[Project Number] 20001638

[Ministry name] Ministry of Trade, Industry and Energy-Ministry ofScience and Technology Information and Communication-Ministry of Healthand Welfare-Ministry of Food and Drug Safety

[Project Management (Special) Institution Name] Korea EvaluationInstitute of Industrial Technology

[Research Project Name] Artificial Intelligence Bio-Robot MedicalConvergence Project

[Research Subject Name] Development of artificial intelligenceassistance and semiautonomous robot system for cardiovascularintervention based on cardiovascular big data

[Managing Department] Seoul Asan Medical Center

[Research Period] May 1, 2018 to Dec. 31, 2020

[Project Unique Number] 1711117085

[Project Number] 2020-0-00159

[Ministry name] Ministry of Science and ICT

[Project Management (Special) Institution Name] Institute forInformation & Communication Technology Planning & Evaluation (IITP)

[Research Project Name] Artificial Intelligence Convergence LeadingProject

[Research Subject Name] Development of AI-based automated cardiovasculardisease diagnosis assistance and surgical tool recommendation system

[Managing Department] Medipixel Co., Ltd.

[Research Period] Apr. 1, 2020 to Dec. 31, 2021

[Project Unique Number] 1425133196

[Project Number] S2758883

[Ministry name] Ministry of SMEs and Startups

[Project Management (Special) Institution Name] Korea Technology &Information Promotion Agency for SMEs

[Research Project Name] Development of Start-up Growth Technology (R&D)

[Research Subject Name] Development of AI-based total occlusionthrombolytic assistance system

[Managing Department] Medipixel Co., Ltd.

[Research Period] Jun. 1, 2019 to May 31, 2020

[Project Unique Number] 1711106903

[Project Number] 2020R1C1C1010470

[Ministry name] Ministry of Science and ICT

[Project Management (Special) Institution Name] National ResearchFoundation of Korea

[Research Project Name] New Researcher Training Support Project

[Research Subject Name] Development of cardiovascular diagnosis methodusing deep learning-based intravascular ultrasound image segmentationtechnology

[Managing Department] University of Ulsan

[Research Period] Mar. 1, 2020 to Feb. 28, 2021

The example embodiments described above may be implemented in hardwarecomponents, software components, and/or combinations of hardwarecomponents and software components. For example, the device, the method,and the components described in the example embodiments may beimplemented using, for example, one or more general-purpose computers orspecial-purpose computers, such as a processor, a controller, anarithmetic logic unit (ALU), a digital signal processor, amicrocomputer, a field programmable gate array (FPGA), a programmablelogic unit (PLU), a microprocessor, or other any devices capable ofexecuting and responding instructions. The processing device may performan operating system OS and one or more software applications performedon the operating system. In addition, the processing device may alsoaccess, store, manipulate, process, and generate data in response toexecution of software. For convenience of understanding, one processingdevice may be described to be used, but it can be seen to those skilledin the art that the processing device may include a plurality ofprocessing elements and/or a plurality types of processing elements. Forexample, the processing device may include a plurality of processors orone processor and one controller. In addition, other processingconfigurations, such as a parallel processor (parallel processor) arealso possible.

Software may include computer programs, codes, instructions, or one ormore combinations thereof, and may configure the processing device tooperate as desired, or to instruct independently or collectively theprocessing device. Software and/or data are interpreted by theprocessing device or may be permanently or temporarily embodied in anytype of machines, components, physical devices, virtual equipment,computer storage media or devices, or signal waves to be transmitted, inorder to provide commands or data to the processing device. The softwaremay be distributed on a computer system connected via a network, and maybe stored or executed in a distributed method. The software and data maybe stored in one or more computer readable recording media.

The method according to the example embodiment may be implemented in aform of program instructions which may be performed through variouscomputer means to be recorded in computer readable media. The computerreadable medium may include program instructions, data files, datastructures, and the like alone or in combination. The programinstructions recorded in the medium may be specially designed andconfigured for the example embodiments or may be publicly known to andused by those skilled in the computer software art. Examples of thecomputer readable record media include magnetic media, such as a harddisk, a floppy disk, and a magnetic tape, optical media such as a CD-ROMand a DVD, magneto-optical media such as a floptical disk, and hardwaredevices such as a ROM, a RAM, and a flash memory, which are speciallyconfigured to store and execute the program instructions. Examples ofthe program instructions include high language codes executable by acomputer using an interpreter and the like, as well as machine languagecodes created by a compiler. The hardware devices may be configured tooperate as one or more software modules in order to perform theoperations of the embodiments, and vice versa.

As described above, although the example embodiments have been describedby the restricted drawings, various modifications and variations can beapplied on the basis of the example embodiments by those skilled in theart. For example, even if the described techniques are performed in adifferent order from the described method, and/or components such as asystem, a structure, a device, a circuit, and the like described aboveare coupled or combined in a different form from the described method,or replaced or substituted by other components or equivalents, anappropriate result can be achieved.

The invention claimed is:
 1. A method for processing a blood vessel image performed by a processor, comprising the steps of: extracting a target blood vessel from a blood vessel image; determining a region of interest (ROI) in an extraction result of the target blood vessel on the basis of a first input received from a user; identifying a first error portion from the extraction result of the target blood vessel in response to the determining of the ROI and providing the user with a correction result of the first error portion; and identifying and correcting a second error portion in the extraction result on the basis of a plurality of points of a second input received from the user in response to a case where the second input is detected from the plurality of points within the ROI where the first error portion is corrected, wherein correcting the second error portion on the basis of the plurality of points further comprises: determining a blood vessel branch located out of a region corresponding to the movement trajectory of the second input among the blood vessel branches connected with the branch point as a misidentification portion, in response to a case where the point corresponding to the second input moves to a region out of the target blood vessel from the branch point within the region extracted as the target blood vessel; and replacing the blood vessel branch with a blood vessel branch indicated by the second input out of the target blood vessel and correcting the remaining extraction result on the basis of the replaced blood vessel branch.
 2. The method for processing the blood vessel image of claim 1, wherein the determining of the ROI comprises determining a shape of the ROI on the basis of points in which the first input is detected.
 3. The method for processing the blood vessel image of claim 1, wherein the correcting of the second error portion on the basis of the plurality of points comprises detecting whether there is a discontinuity portion in points through which the second input passes, while a point corresponding to the second input moves along a region extracted as the target blood vessel; and connecting discontinued portions along a movement trajectory of the second input in response to a case where the discontinuity portion is detected.
 4. The method for processing the blood vessel image of claim 1, wherein the providing of the user with the correction result of the first error portion further comprises providing the user with one or more candidate branches in response to a case where the first error portion is a misidentification portion; and replacing a branch corresponding to the first error portion with the selected branch in response to a case of receiving a pointing input for one branch among the one or more candidate branches from the user.
 5. The method for processing the blood vessel image of claim 1, wherein the providing of the user with the correction result of the first error portion comprises connecting a region corresponding to a blood vessel branch corresponding to a start point of a user input and a region corresponding to a blood vessel branch corresponding to an end point of the user input, in response to a case where the user input is detected in a plurality of points with respect to the correction result.
 6. The method for processing the blood vessel image of claim 1, wherein the providing of the user with the correction result of the first error portion comprises identifying the first error portion on the basis of at least one of blood vessel structure data related to the target blood vessel, curvature information of the target blood vessel, diameter information of the target blood vessel, and brightness information of the target blood vessel, in response to a case where the ROI is determined.
 7. The method for processing the blood vessel image of claim 1, wherein the providing of the user with the correction result of the first error portion comprises providing the user with the correction result of correcting the first error portion on the basis of at least one of blood vessel structure data related to the target blood vessel, curvature information of the target blood vessel, diameter information of the target blood vessel, and brightness information of the target blood vessel, in response to a case where the error portion is identified.
 8. The method for processing the blood vessel image of claim 1, wherein the providing of the user with the correction result of the first error portion comprises generating a plurality of new extraction results for the target blood vessel in response to a case where the first error portion is identified; and selecting one extraction result indicated by the selection input among the plurality of new extraction results in response to the selection input of the user.
 9. A device for processing the blood vessel image comprising: an image receiver for receiving a blood vessel image; and a processor for extracting a target blood vessel from a blood vessel image, determining a region of interest (ROI) in an extraction result of the target blood vessel on the basis of a first input received from a user, identifying a first error portion from the extraction result of the target blood vessel in response to the determining of the ROI and providing the user with a correction result of the first error portion, and identifying and correcting a second error portion in the extraction result on the basis of (a) a plurality of points of a second input received from the user in response to a case where the second input is detected from the plurality of points within the ROI where the first error portion is corrected, (b) determining a blood vessel branch located out of a region corresponding to the movement trajectory of the second input among the blood vessel branches connected with the branch point as a misidentification portion, in response to a case where the point corresponding to the second input moves to a region out of the target blood vessel from the branch point within the region extracted as the target blood vessel, and (c) replacing the blood vessel branch with a blood vessel branch indicated by the second input out of the target blood vessel and correcting the remaining extraction result on the basis of the replaced blood vessel branch. 